Evidence map›Paper›PMID 11768290›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2001

A stochastic model describes the heterogeneous pharmacokinetics of cyclosporin.

L Claret, A Iliadis, P Macheras

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2001. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 17% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. How to avoid unbounded drug accumulation with fractional pharmacokinetics.Journal of pharmacokinetics and pharmacodynamics · 2013
    Article
  4. Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 3 countries.

L ClaretChair of Population Pharmacokinetics, Faculty of Pharmacy, University of Montreal, Canada. claret@pharm.umontreal.ca
A Iliadis
P Macheras
Institut de Neurobiologie de la Méditerranée · FRNational and Kapodistrian University of Athens · GRUniversité de Montréal · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pharmacokinetics of cyclosporin (CsA) are unusual because of several heterogeneous features which include the presence of more than one conformer, considerable accumulation in erythrocytes and lipoproteins, extensive plasma protein binding, distribution into deep tissues, biliary secretion and hepatic clearance involving a large number of metabolites. In this study, a stochastic compartmental model was developed to describe the heterogeneous elimination kinetics of CsA. This new approach relies on a probabilistic transfer model with a gamma distributed probability intensity coefficient for drug elimination. For comparative purposes both the stochastic model and compartmental deterministic models were fitted to real post infusion data from patients receiving CsA as a 2-hr intravenous infusion. The criteria for selecting the best model showed that the stochastic model, although simpler than the compartmental deterministic models, is more flexible and gives a better fit to the kinetic data of CsA than the compartmental deterministic models. The stochastic model with a random rate intensity coefficient adequately describes the heterogeneous pharmacokinetics of CsA.

Indexed as

Models, BiologicalCyclosporineImmunosuppressive AgentsModels, ChemicalProbabilityStochastic ProcessesCyclosporineImmunosuppressive Agents

Identifiers

PMID11768290
OpenAlexW154514314

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.